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<div class="colorscripter-code" style="color:#010101;font-family:Consolas, 'Liberation Mono', Menlo, Courier, monospace !important; position:relative !important;overflow:auto"><table class="colorscripter-code-table" style="margin:0;padding:0;border:none;background-color:#fafafa;border-radius:4px;" cellspacing="0" cellpadding="0"><tr><td style="padding:6px;border-right:2px solid #e5e5e5"><div style="margin:0;padding:0;word-break:normal;text-align:right;color:#666;font-family:Consolas, 'Liberation Mono', Menlo, Courier, monospace !important;line-height:130%"><div style="line-height:130%">1</div><div style="line-height:130%">2</div><div style="line-height:130%">3</div><div style="line-height:130%">4</div><div style="line-height:130%">5</div><div style="line-height:130%">6</div><div style="line-height:130%">7</div><div style="line-height:130%">8</div><div style="line-height:130%">9</div><div style="line-height:130%">10</div><div style="line-height:130%">11</div><div style="line-height:130%">12</div><div style="line-height:130%">13</div><div style="line-height:130%">14</div><div style="line-height:130%">15</div><div style="line-height:130%">16</div><div style="line-height:130%">17</div><div style="line-height:130%">18</div><div style="line-height:130%">19</div><div style="line-height:130%">20</div><div style="line-height:130%">21</div></div></td><td style="padding:6px 0;text-align:left"><div style="margin:0;padding:0;color:#010101;font-family:Consolas, 'Liberation Mono', Menlo, Courier, monospace !important;line-height:130%"><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#999999">#</span></div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#999999"># 따라하며 배우는 파이썬과 데이터과학(생능출판사 2020)</span></div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#999999"># 14.18 k-NN 알고리즘을 적용해보자, 388쪽</span></div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#999999">#</span></div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#999999"># (80:20)으로 분할한다. </span></div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#a71d5d">from</span> sklearn.datasets <span style="color:#a71d5d">import</span> load_iris </div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#a71d5d">from</span> sklearn.model_selection <span style="color:#a71d5d">import</span> train_test_split </div><div style="padding:0 6px; white-space:pre; line-height:130%"> </div><div style="padding:0 6px; white-space:pre; line-height:130%">iris <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> load_iris() </div><div style="padding:0 6px; white-space:pre; line-height:130%">X_train,X_test,y_train,y_test <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> train_test_split(iris.data, iris.target,</div><div style="padding:0 6px; white-space:pre; line-height:130%"> test_size<span style="color:#0086b3"></span><span style="color:#a71d5d">=</span><span style="color:#0099cc">0.</span><span style="color:#0099cc">2</span>)</div><div style="padding:0 6px; white-space:pre; line-height:130%"> </div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#a71d5d">from</span> sklearn.neighbors <span style="color:#a71d5d">import</span> KNeighborsClassifier </div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#a71d5d">from</span> sklearn <span style="color:#a71d5d">import</span> metrics </div><div style="padding:0 6px; white-space:pre; line-height:130%"> </div><div style="padding:0 6px; white-space:pre; line-height:130%">num_neigh <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> <span style="color:#0099cc">3</span></div><div style="padding:0 6px; white-space:pre; line-height:130%">knn <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> KNeighborsClassifier(n_neighbors <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> num_neigh) </div><div style="padding:0 6px; white-space:pre; line-height:130%">knn.fit(X_train, y_train) </div><div style="padding:0 6px; white-space:pre; line-height:130%">y_pred <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> knn.predict(X_test) </div><div style="padding:0 6px; white-space:pre; line-height:130%">scores <span style="color:#0086b3"></span><span style="color:#a71d5d">=</span> metrics.accuracy_score(y_test, y_pred) </div><div style="padding:0 6px; white-space:pre; line-height:130%"><span style="color:#066de2">print</span>(<span style="color:#63a35c">'n_neighbors가 {0:d}일때 정확도: {1:.3f}'</span>.<span style="color:#066de2">format</span>(num_neigh, scores))</div></div></td><td style="vertical-align:bottom;padding:0 2px 4px 0"><a href="http://colorscripter.com/info#e" target="_blank" style="text-decoration:none;color:white"><span style="font-size:9px;word-break:normal;background-color:#e5e5e5;color:white;border-radius:10px;padding:1px">cs</span></a></td></tr></table></div>
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